13. ICONIP 2006: Hong Kong, China

Neurobiological Modeling and Analysis

• Colin Molter, Naoyuki Sato, Utku Salihoglu, Yoko Yamaguchi:
  How Reward Can Induce Reverse Replay of Behavioral Sequences in the Hippocampus. 1-10
  
• Meng Hu, Jiaojie Li, Guang Li, Walter J. Freeman:
  Analysis of Early Hypoxia EEG Based on a Novel Chaotic Neural Network. 11-18
  
• Hiroki Kurashige, Yutaka Sakai:
  BCM-Type Synaptic Plasticity Model Using a Linear Summation of Calcium Elevations as a Sliding Threshold. 19-29
  
• Guang-Li Wang, Xue Liu, Pu-Ming Zhang, Pei-Ji Liang:
  A New Method for Multiple Spike Train Analysis Based on Information Discrepancy. 30-38
  
• Ryosuke Hosaka, Tohru Ikeguchi, Kazuyuki Aihara:
  Self-organizing Rhythmic Patterns with Spatio-temporal Spikes in Class I and Class II Neural Networks. 39-48
  
• Toshio Akimitsu, Akira Hirose, Yoichi Okabe:
  Self-organization Through Spike-Timing Dependent Plasticity Using Localized Synfire-Chain Patterns. 49-58
  
• Wuyin Jin, Zhiyuan Rui, Yaobing Wei, Changfeng Yan:
  Comparison of Spike-Train Responses of a Pair of Coupled Neurons Under the External Stimulus. 59-64
  
• Ling Fu Meng, Chiu-Ping Lu, Bo-Wei Chen, Ching-Horng Chen:
  Fatigue-Induced Reversed Hemispheric Plasticity During Motor Repetitions: A Brain Electrophysiological Study. 65-71
  
• Minoru Tsukada, Yoshiyuki Yamazaki:
  Functional Differences Between the Spatio-temporal Learning Rule (STLR) and Hebb Type (HEBB) in Single Pyramidal Cells in the Hippocampal CA1 Area. 72-81
  
• Akhil R. Garg, Basabi Bhaumik:
  Ratio of Average Inhibitory to Excitatory Conductance Modulates the Response of Simple Cell. 82-89
  
• Beata Grzyb, Jacek Bialowas:
  Modeling of LTP-Related Phenomena Using an Artificial Firing Cell. 90-96
  
• Kai Yin, Xiao-jie Zhao, Li Yao:
  Time Variant Causality Model Applied in Brain Connectivity Network Based on Event Related Potential. 97-104
  
• Alan Rosen, David B. Rosen:
  An Electromechanical Neural Network Robotic Model of the Human Body and Brain: Sensory-Motor Control by Reverse Engineering Biological Somatic Sensors. 105-116
  

Cognitive Processing

• Toshikazu Samura, Motonobu Hattori, Shun Ishizaki:
  Sequence Disambiguation by Functionally Divided Hippocampal CA3 Model. 117-126
  
• Xiaodi Hou, Liqing Zhang:
  A Time-Dependent Model of Information Capacity of Visual Attention. 127-136
  
• Abdelhamid Bouchachia:
  Learning with Incrementality. 137-146
  
• Fumiko Tanabe, Ken Mogi:
  Lability of Reactivated Human Declarative Memory. 147-154
  
• Sintiani Dewi Teddy, Edmund Ming-Kit Lai, Hiok Chai Quek:
  A Neuropsychologically-Inspired Computational Approach to the Generalization of Cerebellar Learning. 155-164
  
• Osamu Watanabe:
  A Neural Model for Stereo Transparency with the Population of the Disparity Energy Models. 165-174
  
• Xia Wu, Li Yao, Zhi-ying Long, Jie Lu, Kuncheng Li:
  Functional Connectivity in the Resting Brain: An Analysis Based on ICA. 175-182
  
• Cheng-Yuan Liou, Jau-Chi Huang, Wen-Chie Yang:
  Semantic Addressable Encoding. 183-192
  
• Mei Tian, Siwei Luo, Lingzhi Liao, Lianwei Zhao:
  Top-Down Attention Guided Object Detection. 193-202
  
• Y. Lin, Y. P. Zhang, R. H. Wu, H. Li, Z. W. Shen, X. K. Chen, K. Huang, G. Guo:
  Absolute Quantification of Brain Creatine Concentration Using Long Echo Time PRESS Sequence with an External Standard and LCModel: Verification with in Vitro HPLC Method. 203-210
  
• Ryszard Tadeusiewicz, Andrzej Izworski:
  Learning in Neural Network - Unusual Effects of "Artificial Dreams". 211-218
  
• Nobuhiko Wagatsuma, Ko Sakai:
  Spatial Attention in Early Vision Alternates Direction-of-Figure. 219-227
  
• Fuminori Mizushima, Takashi Toyoshima:
  Language Learnability by Feedback Self-Organizing Maps. 228-236
  
• Jose Ignacio Serrano, M. Dolores del Castillo:
  Text Representation by a Computational Model of Reading. 237-246
  
• Hyungwook Yim, Changsu Park, Heuseok Lim, Kichun Nam:
  Mental Representation and Processing Involved in Comprehending Korean Regular and Irregular Verb Eojeols: An fMRI and Reaction Time Study. 247-254
  
• Hidetaka Morisawa, Daisuke Hirayama, Kazuhisa Fujita, Yoshiki Kashimori, Takeshi Kambara:
  Binding Mechanism of Frequency-Specific ITD and IID Information in Sound Localization of Barn Owl. 255-262
  
• Seiichi Hirooka, Kazuhisa Fujita, Yoshiki Kashimori:
  Effect of Feedback Signals on Tuning Shifts of Subcortical Neurons in Echolocation of Bat. 263-271
  
• Tian Guan, Qin Gong, Datian Ye:
  A Novel Speech Processing Algorithm for Cochlear Implant Based on Selective Fundamental Frequency Control. 272-279
  
• Emad A. M. Andrews Shenouda, Quaid Morris, Anthony J. Bonner:
  Connectionist Approaches for Predicting Mouse Gene Function from Gene Expression. 280-289
  
• Gisoon Yu, Choong-Myung Kim, Dong Hwee Kim, Kichun Nam:
  Semantic Activation and Cortical Areas Related to the Lexical Ambiguity and Idiomatic Ambiguity. 290-297
  
• Wojciech Kacalak, Maciej Majewski:
  Intelligent System for Automatic Recognition and Evaluation of Speech Commands. 298-305
  
• Rubin Wang, Zhikang Zhang:
  A New Mechanism on Brain Information Processing - Energy Coding. 306-313
  

Mathematical Modeling and Analysis

• Man-Wai Mak, Sun-Yuan Kung:
  A Solution to the Curse of Dimensionality Problem in Pairwise Scoring Techniques. 314-323
  
• C. F. Lo, T. K. Chung:
  First Passage Time Problem for the Ornstein-Uhlenbeck Neuronal Model. 324-331
  
• Zhan Shu, James Lam:
  Delay-Dependent Exponential Estimates of Stochastic Neural Networks with Time Delay. 332-341
  
• Xiang Peng, Irwin King:
  Imbalanced Learning in Relevance Feedback with Biased Minimax Probability Machine for Image Retrieval Tasks. 342-351
  
• Takashi Saeki, Tsutomu Miki:
  Improvement of the Perfect Recall Rate of Block Splitting Type Morphological Associative Memory Using a Majority Logic Approach. 352-360
  
• Colin Fyfe, Gayle Leen:
  Two Methods for Sparsifying Probabilistic Canonical Correlation Analysis. 361-370
  
• Saejoon Kim:
  Turbo Decoding as an Instance of Expectation Maximization Algorithm. 371-378
  
• Wenlian Lu, Tianping Chen:
  Dynamical Behaviors of a Large Class of Delayed Differential Systems with Discontinuous Right-Hand Side. 379-386
  
• Hiroaki Arie, Jun Namikawa, Tetsuya Ogata, Jun Tani, Shigeki Sugano:
  Reinforcement Learning Algorithm with CTRNN in Continuous Action Space. 387-396
  
• Masahiro Nakagawa:
  Entropy Based Associative Model. 397-406
  
• Tikara Hosino, Kazuho Watanabe, Sumio Watanabe:
  Free Energy of Stochastic Context Free Grammar on Variational Bayes. 407-416
  
• Yu Nishiyama, Sumio Watanabe:
  Asymptotic Behavior of Stochastic Complexity of Complete Bipartite Graph-Type Boltzmann Machines. 417-426
  
• Raphael V. Carneiro, Stiven Schwanz Dias, Dijalma Fardin, Hallysson Oliveira, Artur S. d'Avila Garcez, Alberto Ferreira de Souza:
  Improving VG-RAM Neural Networks Performance Using Knowledge Correlation. 427-436
  
• Jinhyuk Choi, Geehyuk Lee:
  The Bifurcating Neuron Network 3 as Coloring Problem Solver and N-Ary Associative Memory. 437-446
  
• Hui Kong, Jian-Gang Wang:
  Coupling Adaboost and Random Subspace for Diversified Fisher Linear Discriminant. 447-456
  
• Hengqing Tong, Li Xiong, Hui Peng:
  Self-organized Path Constraint Neural Network: Structure and Algorithm. 457-466
  
• Yao-qun Xu, Ming Sun, Ji-hong Shen:
  Gauss Wavelet Chaotic Neural Networks. 467-476
  
• Mercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa:
  Training RBFs Networks: A Comparison Among Supervised and Not Supervised Algorithms. 477-486
  
• SeungGwan Lee:
  A Cooperation Online Reinforcement Learning Approach in Ant-Q. 487-494
  
• Haiqing Wang, Daoying Pi, Ning Jiang, Steven X. Ding:
  Soft Analyzer Modeling for Dearomatization Unit Using KPCR with Online Eigenspace Decomposition. 495-504
  
• Vajpai Jayashri, J. B. Arun:
  A Soft Computing Based Approach for Modeling of Chaotic Time Series. 505-512
  
• Yatong Zhou, Taiyi Zhang, Xiaohe Li:
  Predicting Nonstationary Time Series with Multi-scale Gaussian Processes Model. 513-520
  
• John Sum, Andrew Chi-Sing Leung, Kevin Ho:
  Prediction Error of a Fault Tolerant Neural Network. 521-528
  
• Wudai Liao, Dongyun Wang, Yulin Xu, Xiaoxin Liao:
  Delay-Dependent and Delay-Independent Stability Conditions of Delayed Cellular Neural Networks. 529-536
  
• Ke Zhang, Sadayuki Murashima:
  The Perfect Recalling Rate of Morphological Associative Memory. 537-546
  
• Akio Kawana, Shinya Tsuzuki, Osamu Watanabe:
  Analysis of Dynamics of Cultured Neuronal Networks Using I&F Model. 547-553
  
• Run-Nian Ma, Guo-Qiang Bai:
  Convergence Study of Discrete Neural Networks with Delay. 554-561
  
• Wei Wu, Hongmei Shao, Zhengxue Li:
  Convergence of Batch BP Algorithm with Penalty for FNN Training. 562-569
  
• Zeynep Orman, Sabri Arik:
  New Results for Global Stability of Cohen-Grossberg Neural Networks with Discrete Time Delays. 570-579
  
• Weirui Zhao, Huanshui Zhang:
  Global Stability of Cohen-Grossberg Neural Networks with Distributed Delays. 580-590
  
• Chaojin Fu, Zhongsheng Wang:
  Exponential Stability of Neural Networks with Distributed Time Delays and Strongly Nonlinear Activation Functions. 591-597
  
• Yonggui Kao, Cunchen Gao, Lu Wu, Qinghe Ming:
  Global Stability of Bidirectional Associative Memory Neural Networks with Variable Coefficients and S-Type Distributed Delays. 598-607
  
• Deepak Mishra, Arvind Tolambiya, Amit Shukla, Prem Kumar Kalra:
  Stability Analysis for Higher Order Complex-Valued Hopfield Neural Network. 608-615
  

Learning Algorithms

• Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
  Mixture of Neural Networks: Some Experiments with the Multilayer Feedforward Architecture. 616-625
  
• Ryotaro Kamimura, Fumihiko Yoshida, Ryozo Kitajima:
  Collective Information-Theoretic Competitive Learning: Emergency of Improved Performance by Collectively Treated Neurons. 626-633
  
• Chuanhuan Yin, Shengfeng Tian, Shaomin Mu:
  A Fast Bit-Parallel Algorithm for Gapped String Kernels. 634-641
  
• Bo Shao, Zhitong Cao, Yuetong Xu:
  A RBFN Based Cogging Force Estimator of PMLSM with q<1 Structure. 642-649
  
• Shingo Takamatsu, Shinichi Nakajima, Sumio Watanabe:
  Localized Bayes Estimation for Non-identifiable Models. 650-659
  
• Hengqing Tong, Yanfang Deng, Ziling Li:
  Optimality of Kernel Density Estimation of Prior Distribution in Bayes Network. 660-669
  
• Kyu Baek Hwang, Byoung-Hee Kim, Byoung-Tak Zhang:
  Learning Hierarchical Bayesian Networks for Large-Scale Data Analysis. 670-679
  
• Wang Limin:
  Learning Bayesian-Neural Network from Mixed-Mode Data. 680-687
  
• Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo:
  Adaptive Boosting: Dividing the Learning Set to Increase the Diversity and Performance of the Ensemble. 688-697
  
• Shuichi Kurogi, Shinya Tanaka, Ryohei Koyama, Takeshi Nishida:
  Ensemble of Competitive Associative Nets and a Method to Select an Effective Number of Units. 698-707
  
• Thiago Dutra, Anne M. P. Canuto, Marcílio Carlos Pereira de Souto:
  Using Weighted Combination-Based Methods in Ensembles with Different Levels of Diversity. 708-717
  
• Bingjie Liu, Changhua Hu:
  Integrated Neural Network Ensemble Algorithm Based on Clustering Technology. 718-726
  
• Dmitry Kropotov, Dmitry Vetrov, Nikita Ptashko, Oleg Vasiliev:
  The Use of Stability Principle for Kernel Determination in Relevance Vector Machines. 727-736
  
• Haiqing Wang, Ping Li, Zhi-Huan Song, Steven X. Ding:
  Adaptive Kernel Leaning Networks with Application to Nonlinear System Identification. 737-746
  
• Mauricio A. Álvarez, Ricardo Henao:
  Probabilistic Kernel Principal Component Analysis Through Time. 747-754
  
• Imhoi Koo, Rhee Man Kil:
  Confidence Intervals for the Risks of Regression Models. 755-764
  
• Thanapant Raicharoen, Chidchanok Lursinsap, Frank C. Lin:
  A Divide-and-Conquer Approach to the Pairwise Opposite Class-Nearest Neighbor (POC-NN) Algorithm for Regression Problem. 765-772
  

Support Vector Machines

• Wen Wen, Zhifeng Hao, Zhuangfeng Shao, Xiaowei Yang, Ming Chen:
  A Heuristic Weight-Setting Algorithm for Robust Weighted Least Squares Support Vector Regression. 773-781
  
• Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Hui Zheng, Einar P. V. Wilder-Smith:
  Feature Selection Using SVM Probabilistic Outputs. 782-791
  
• Ha-Nam Nguyen, Syng-Yup Ohn:
  Unified Kernel Function and Its Training Method for SVM. 792-800
  
• Ping Ling, Zhe Wang, Chunguang Zhou:
  A Spectrum-Based Support Vector Algorithm for Relational Data Semi-supervised Classification. 801-810
  
• Bo Chen, Hongwei Liu, Zheng Bao:
  Speeding Up SVM in Test Phase: Application to Radar HRRP ATR. 811-818
  
• Yinshan Jia, Wang Yumei:
  A New Dual nu-Support Vector Machine. 819-826
  
• Jun Guo, Norikazu Takahashi, Tetsuo Nishi:
  A Novel Sequential Minimal Optimization Algorithm for Support Vector Regression. 827-836
  
• Pilsung Kang, Sungzoon Cho:
  EUS SVMs: Ensemble of Under-Sampled SVMs for Data Imbalance Problems. 837-846
  
• Jingmin Wang, Guoqiao Ren:
  A Improved SVM and Its Using in Electric Power System Load Forecasting. 847-855
  
• Qinzhen Xu, Wenjiang Pei, Luxi Yang, Zhenya He:
  Support Vector Machine Tree Based on Feature Selection. 856-863
  
• Sung-Hae Jun, Kyung-Whan Oh:
  A Competitive Co-evolving Support Vector Clustering. 864-873
  
• Zonghai Sun:
  Fuzzy Probability C-Regression Estimation Based on Least Squares Support Vector Machine. 874-881
  
• Jilin Yang, Hong Peng, Zheng Pei:
  Filtering E-Mail Based on Fuzzy Support Vector Machines and Aggregation Operator. 882-891
  
• Jian Cheng, Jian-Sheng Qian, Yi-Nan Guo:
  A Distributed Support Vector Machines Architecture for Chaotic Time Series Prediction. 892-899
  
• Jiancheng Sun, Yatong Zhou, Yaohui Bai, Jianguo Luo:
  Nonlinear Noise Reduction of Chaotic Time Series Based on Multi-dimensional Recurrent Least Squares Support Vector Machines. 900-906
  

Self-Organizing Map

• Takeshi Yamakawa, Keiichi Horio, Masaharu Hoshino:
  Self-Organizing Map with Input Data Represented as Graph. 907-914
  
• Arthur L. Hsu, Saman K. Halgamuge:
  Semi-supervised Learning of Dynamic Self-Organising Maps. 915-924
  
• Ryotaro Kamimura:
  Self-organizing by Information Maximization: Realizing Self-Organizing Maps by Information-Theoretic Competitive Learning. 925-934
  
• Shuhei Nishida, Kazuo Ishii, Tetsuo Furukawa:
  An Online Adaptation Control System Using mnSOM. 935-942
  
• Tetsuo Furukawa, Kazuhiro Tokunaga:
  Generalization of the Self-Organizing Map: From Artificial Neural Networks to Artificial Cortexes. 943-949
  
• Tetsuo Furukawa:
  SOM of SOMs: An Extension of SOM from 'Map' to 'Homotopy'. 950-957
  
• Kazuhiro Tokunaga, Tetsuo Furukawa:
  Modular Network SOM: Theory, Algorithm and Applications. 958-967
  
• Takeshi Yamakawa, Keiichi Horio, Takahiro Tanaka:
  Evaluation-Based Topology Representing Network for Accurate Learning of Self-Organizing Relationship Network. 968-977
  
• Yuexian Hou, Gong Kefei, Pilian He:
  Adaptively Incremental Self-organizing Isometric Embedding. 978-986
  
• Shuzhong Yang, Siwei Luo, Jianyu Li:
  An Extended Model on Self-Organizing Map. 987-994
  
• Manuel Martín-Merino, Jesus Román:
  A New SOM Algorithm for Electricity Load Forecasting. 995-1003
  
• Tetsunari Oshime, Toshimichi Saito, Hiroyuki Torikai:
  ART-Based Parallel Learning of Growing SOMs and Its Application to TSP. 1004-1011
  
• Cheng-Yuan Liou, Yen-Ting Kuo, Jau-Chi Huang:
  Smooth Seamless Surface Construction Based on Conformal Self-organizing Map. 1012-1021
  
• Lijuan Huang:
  Consumer's Purchasing Behavior Analysis Based on the Self-Organizing Feature Map Neural Network Algorithm in E-Supply Chain. 1022-1029
  
• Shiyuan Liu, Li Lu, Guanglan Liao, Jianping Xuan:
  Pattern Discovery from Time Series Using Growing Hierarchical Self-Organizing Map. 1030-1037
  

Independent Component Analysis and Blind Source Separation

• Zhaoshui He, Andrzej Cichocki, Shengli Xie:
  K-Hyperplanes Clustering and Its Application to Sparse Component Analysis. 1038-1047
  
• Ingo R. Keck, Jan Churan, Fabian J. Theis, Peter Gruber, Elmar Wolfgang Lang, Carlos García Puntonet:
  Region of Interest Based Independent Component Analysis. 1048-1057
  
• Qinghua Huang, Jie Yang, Yue Zhou:
  Variational Bayesian Method for Temporally Correlated Source Separation. 1058-1067
  
• Hao Shen, Knut Hüper, Alexander J. Smola:
  Newton-Like Methods for Nonparametric Independent Component Analysis. 1068-1077
  
• Chan-Cheng Liu, Tsung-Ying Sun, Sheng-Ta Hsieh, Chun-Ling Lin, Kan-Yuan Lee:
  A Hybrid Blind Signal Separation Algorithm: Particle Swarm Optimization on Feed-Forward Neural Network. 1078-1087
  
• Tahir Rasheed, Myung Ho In, Young-Koo Lee, Sungyoung Lee, Soo Yeol Lee, Tae-Seong Kim:
  Constrained ICA Based Ballistocardiogram and Electro-Oculogram Artifacts Removal from Visual Evoked Potential EEG Signals Measured Inside MRI. 1088-1097
  
• Mao Ye, Xuqian Fan, Qihe Liu:
  Monotonic Convergence of a Nonnegative ICA Algorithm on Stiefel Manifold. 1098-1106
  
• Fasong Wang, Hongwei Li, Rui Li:
  Exterior Penalty Function Method Based ICA Algorithm for Hybrid Sources Using GKNN Estimation. 1107-1116
  
• Yinghong Luo, Caixia Tao, Xiaohu Qiang, Xiang-Yan Zeng:
  Denoising by Anisotropic Diffusion of Independent Component Coefficients. 1117-1124
  
• Beihai Tan, Xiaolu Li:
  Blind Separation of Digital Signal Sources in Noise Circumstance. 1125-1132
  
• Chandra Shekhar Dhir, Hyung-Min Park, Soo-Young Lee:
  Performance Evaluation of Directionally Constrained Filterbank ICA on Blind Source Separation of Noisy Observations. 1133-1142
  
• C. F. Lo, T. K. Chung:
  First Passage Time Problem for the Ornstein-Uhlenbeck Neuronal Model. 1155-1164
  

Last update Tue Feb 14 04:02:05 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page